Add period to evaluation monitor. (#6348)
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@ -583,12 +583,18 @@ class EvaluationMonitor(TrainingCallback):
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Extra user defined metric.
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rank : int
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Which worker should be used for printing the result.
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period : int
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How many epoches between printing.
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show_stdv : bool
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Used in cv to show standard deviation. Users should not specify it.
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'''
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def __init__(self, rank=0, show_stdv=False):
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def __init__(self, rank=0, period=1, show_stdv=False):
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self.printer_rank = rank
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self.show_stdv = show_stdv
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self.period = period
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assert period > 0
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# last error message, useful when early stopping and period are used together.
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self._lastest = None
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super().__init__()
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def _fmt_metric(self, data, metric, score, std):
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@ -601,6 +607,7 @@ class EvaluationMonitor(TrainingCallback):
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def after_iteration(self, model, epoch, evals_log):
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if not evals_log:
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return False
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msg = f'[{epoch}]'
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if rabit.get_rank() == self.printer_rank:
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for data, metric in evals_log.items():
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@ -613,9 +620,20 @@ class EvaluationMonitor(TrainingCallback):
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stdv = None
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msg += self._fmt_metric(data, metric_name, score, stdv)
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msg += '\n'
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if (epoch % self.period) != 0:
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rabit.tracker_print(msg)
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self._lastest = None
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else:
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# There is skipped message
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self._lastest = msg
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return False
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def after_training(self, model):
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if rabit.get_rank() == self.printer_rank and self._lastest is not None:
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rabit.tracker_print(self._lastest)
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return model
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class TrainingCheckPoint(TrainingCallback):
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'''Checkpointing operation.
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@ -92,7 +92,8 @@ def _train_internal(params, dtrain,
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assert all(isinstance(c, callback.TrainingCallback)
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for c in callbacks), "You can't mix new and old callback styles."
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if verbose_eval:
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callbacks.append(callback.EvaluationMonitor())
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verbose_eval = 1 if verbose_eval is True else verbose_eval
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callbacks.append(callback.EvaluationMonitor(period=verbose_eval))
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if early_stopping_rounds:
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callbacks.append(callback.EarlyStopping(
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rounds=early_stopping_rounds, maximize=maximize))
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@ -485,7 +486,9 @@ def cv(params, dtrain, num_boost_round=10, nfold=3, stratified=False, folds=None
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assert all(isinstance(c, callback.TrainingCallback)
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for c in callbacks), "You can't mix new and old callback styles."
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if isinstance(verbose_eval, bool) and verbose_eval:
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callbacks.append(callback.EvaluationMonitor(show_stdv=show_stdv))
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verbose_eval = 1 if verbose_eval is True else verbose_eval
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callbacks.append(callback.EvaluationMonitor(period=verbose_eval,
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show_stdv=show_stdv))
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if early_stopping_rounds:
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callbacks.append(callback.EarlyStopping(
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rounds=early_stopping_rounds, maximize=maximize))
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@ -11,7 +11,7 @@ import sys
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from test_gpu_pickling import build_dataset, model_path, load_pickle
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sys.path.append("tests/python")
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import test_basic as tb
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import testing as tm
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class TestLoadPickle(unittest.TestCase):
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@ -61,7 +61,7 @@ class TestLoadPickle(unittest.TestCase):
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rng = np.random.RandomState(1994)
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X = rng.randn(10, 10)
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y = rng.randn(10)
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with tb.captured_output() as (out, err):
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with tm.captured_output() as (out, err):
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# Test no thrust exception is thrown
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with pytest.raises(xgb.core.XGBoostError):
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xgb.train({'tree_method': 'gpu_hist'}, xgb.DMatrix(X, y))
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@ -7,13 +7,12 @@ import os
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import sys
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import json
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import pytest
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import xgboost as xgb
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from xgboost import XGBClassifier
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sys.path.append("tests/python")
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import testing as tm
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import xgboost as xgb
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from xgboost import XGBClassifier
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model_path = './model.pkl'
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@ -1,7 +1,4 @@
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# -*- coding: utf-8 -*-
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import sys
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from contextlib import contextmanager
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from io import StringIO
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import numpy as np
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import os
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import xgboost as xgb
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@ -9,29 +6,12 @@ import unittest
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import json
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from pathlib import Path
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import tempfile
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import testing as tm
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dpath = 'demo/data/'
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rng = np.random.RandomState(1994)
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@contextmanager
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def captured_output():
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"""Reassign stdout temporarily in order to test printed statements
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Taken from:
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https://stackoverflow.com/questions/4219717/how-to-assert-output-with-nosetest-unittest-in-python
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Also works for pytest.
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"""
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new_out, new_err = StringIO(), StringIO()
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old_out, old_err = sys.stdout, sys.stderr
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try:
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sys.stdout, sys.stderr = new_out, new_err
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yield sys.stdout, sys.stderr
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finally:
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sys.stdout, sys.stderr = old_out, old_err
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class TestBasic(unittest.TestCase):
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def test_compat(self):
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from xgboost.compat import lazy_isinstance
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@ -181,7 +161,6 @@ class TestBasic(unittest.TestCase):
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assert dm.num_row() == row
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assert dm.num_col() == cols
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def test_cv(self):
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dm = xgb.DMatrix(dpath + 'agaricus.txt.train')
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params = {'max_depth': 2, 'eta': 1, 'verbosity': 0,
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@ -236,7 +215,7 @@ class TestBasic(unittest.TestCase):
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print([fold.dtest.get_label() for fold in cbackenv.cvfolds])
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# Run cross validation and capture standard out to test callback result
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with captured_output() as (out, err):
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with tm.captured_output() as (out, err):
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xgb.cv(
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params, dm, num_boost_round=1, folds=folds, callbacks=[cb],
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as_pandas=False
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@ -257,7 +236,6 @@ class TestBasicPathLike(unittest.TestCase):
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assert dtrain.num_row() == 6513
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assert dtrain.num_col() == 127
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def test_DMatrix_save_to_path(self):
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"""Saving to a binary file using pathlib from a DMatrix."""
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data = np.random.randn(100, 2)
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@ -34,10 +34,27 @@ class TestCallbacks(unittest.TestCase):
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num_boost_round=rounds,
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evals_result=evals_result,
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verbose_eval=True)
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print('evals_result:', evals_result)
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assert len(evals_result['Train']['error']) == rounds
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assert len(evals_result['Valid']['error']) == rounds
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with tm.captured_output() as (out, err):
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xgb.train({'objective': 'binary:logistic',
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'eval_metric': 'error'}, D_train,
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evals=[(D_train, 'Train'), (D_valid, 'Valid')],
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num_boost_round=rounds,
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evals_result=evals_result,
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verbose_eval=2)
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output: str = out.getvalue().strip()
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pos = 0
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msg = 'Train-error'
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for i in range(rounds // 2):
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pos = output.find('Train-error', pos)
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assert pos != -1
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pos += len(msg)
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assert output.find('Train-error', pos) == -1
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def test_early_stopping(self):
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D_train = xgb.DMatrix(self.X_train, self.y_train)
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D_valid = xgb.DMatrix(self.X_valid, self.y_valid)
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@ -2,7 +2,6 @@ import collections
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import importlib.util
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import numpy as np
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import xgboost as xgb
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from xgboost.sklearn import XGBoostLabelEncoder
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import testing as tm
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import tempfile
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import os
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@ -11,8 +10,6 @@ import pytest
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import unittest
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import json
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from test_basic import captured_output
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rng = np.random.RandomState(1994)
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pytestmark = pytest.mark.skipif(**tm.no_sklearn())
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@ -872,7 +869,7 @@ def test_parameter_validation():
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reg = xgb.XGBRegressor(foo='bar', verbosity=1)
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X = np.random.randn(10, 10)
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y = np.random.randn(10)
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with captured_output() as (out, err):
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with tm.captured_output() as (out, err):
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reg.fit(X, y)
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output = out.getvalue().strip()
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@ -882,7 +879,7 @@ def test_parameter_validation():
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importance_type='gain', verbosity=1)
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X = np.random.randn(10, 10)
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y = np.random.randn(10)
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with captured_output() as (out, err):
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with tm.captured_output() as (out, err):
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reg.fit(X, y)
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output = out.getvalue().strip()
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@ -1,6 +1,8 @@
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# coding: utf-8
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import os
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import platform
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import sys
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from contextlib import contextmanager
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from io import StringIO
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from xgboost.compat import SKLEARN_INSTALLED, PANDAS_INSTALLED
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from xgboost.compat import DASK_INSTALLED
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import pytest
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@ -281,6 +283,24 @@ class DirectoryExcursion:
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os.remove(f)
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@contextmanager
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def captured_output():
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"""Reassign stdout temporarily in order to test printed statements
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Taken from:
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https://stackoverflow.com/questions/4219717/how-to-assert-output-with-nosetest-unittest-in-python
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Also works for pytest.
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"""
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new_out, new_err = StringIO(), StringIO()
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old_out, old_err = sys.stdout, sys.stderr
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try:
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sys.stdout, sys.stderr = new_out, new_err
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yield sys.stdout, sys.stderr
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finally:
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sys.stdout, sys.stderr = old_out, old_err
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CURDIR = os.path.normpath(os.path.abspath(os.path.dirname(__file__)))
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PROJECT_ROOT = os.path.normpath(
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os.path.join(CURDIR, os.path.pardir, os.path.pardir))
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